Contributed by John Lazar, Software Engineer, Business Leader and Technology Investor

We are assailed almost every day with a new report or study purporting to clarify the impact of Artificial Intelligence (AI) and automation. For someone trying to understand the effect of the change we are undergoing — and make some sense of where we are heading — it is very difficult to find unanimity and coherence amongst the welter of statistics and predictions.

On the one hand, some commentators believe that the AI “revolution” is massively overstated — AI hasn’t actually advanced much since the 1980s, apart from access to a different scale of computational power, and larger datasets — or they posit that the change is just like previous industrial upheavals, in that new jobs will emerge to replace the ones that are lost. And, by the way, AI can’t be having an effect because otherwise, why are productivity figures so low in many industrialised nations?

In complete contrast, others believe that that the revolution is fundamentally different, exponentially rapid and profound: at least 50% of jobs may go in the next decade or so, and Artificial General Intelligence (AGI — a generally intelligent artificial intelligence which outstrips human intelligence) will be with us soon (2050 seems to be the most common prediction). But even these commentators then split between utopian (“Great — leisure for all!”) and dystopian (“Eeek — the robots are coming for all but a few lucky and wealthy ones!”) strands.

How can we step through all this noise and hype with nuance, balance and subtlety, in a way that will allow us to respond appropriately?

Firstly, we should accept that humans are generally not very good at forecasting. Michael Mullany’s recent analysis of the Gartner Hype Cycle for Emerging Technologies is illustrative: he points out that of more than 200 unique technologies that have appeared on the Hype Cycle over the past two decades, just a handful — Cloud Computing, 3D Printing, Natural Language Search, Electronic Ink — have been identified early and travelled even somewhat predictably through the Hype Cycle from start to end. Furthermore — as Amara’s Law states — we tend to overestimate the effect of a technology in the short run and underestimate the effect over the long term. Rodney Brooks of MIT recently showed how GPS is a great example of Amara’s Law in action: 24 GPS satellites were first deployed in 1978, but the program was nearly cancelled multiple times over the next few decades before it was widely used, and now we rely on GPS in ways which were unimagined at first. As Brooks says, “it has seeped into so many aspects of our lives that we would not just be lost if it went away; we would be cold, hungry, and quite possibly dead”.

My conclusion is that short-term predictions about the effects of AI and automation may well be overstated, but over the longer term there are strong indications that the change we are experiencing is “different”, not least because

• while it is easy to over-emphasise the ability of a narrow AI to generalise its learning, AIs are beginning to jump across task boundaries in ways which industrial machinery from the 19th and 20th centuries never did;

• the state of the art is being driven by fertile cross-disciplinary work encompassing computer science, neuro-science, computational biology and philosophy;

• our theories of knowledge and science are struggling to adapt to the reality that we cannot understand and explain how AIs reach conclusions which are clearly valid.

But we are still faced with far more questions than answers, especially about timescales, and in the wake of this uncertainty, we cannot afford to impose solutions which are short-term oriented, historically contoured, narrow, rigid and prescriptive: we should strive for “anti-fragility”.

Secondly, we should be careful of jumping quickly to detailed policy debates and proposals in a way which simply entrenches people in their existing political outlooks and prejudices. Universal Basic Income (UBI) is an excellent case in point. UBI may well turn out to be an efficacious policy intervention — and should be debated fully — but right now when UBI is raised, most people instinctively fall back into historical political positions. People on the traditional Right either support UBI because in their view it will allow the state to be shrunk, or hate it because they don’t like “welfare scroungers”. People on the traditional Left often respond negatively due to a combination of believing in the importance of work, and because some on the Right support UBI.

The best way to avoid these pitfalls is by rebooting and updating our concept of citizenship. Our current view of citizenship is driven by a hyper-economic view of society, and therefore treats citizens primarily as atomised consumers, with “consumer rights”. If we want to develop a common framework to help us think strategically about profound change, we need to go back to first principles — e.g. Socrates, Confucius, Jean-Jacques Rousseau, Thomas Paine, J.S.Mill, Locke, the foundations of modern parliamentary democracy, the UN declaration of human rights… — and then update our conception for the 21st century and beyond, encompassing local, national and global perspectives. Most importantly, this must carefully tease out both rights and responsibilities. We can no longer afford to view ourselves as pure consumers, and it is vital to define the participatory requirement that a new social contract would impose on modern citizens.

This is of course an extremely difficult conversation to have — especially on a global scale, in part due to the varying concepts of citizenship held by different cultures — but if we are able to do it, we can begin to examine the issues thrown up by the Fourth Industrial Revolution, in a far more nuanced and wide-ranging way.

● For a start, we can begin to discuss the notion of “work” in a more rounded fashion. Surely “work” should be defined as activity performed by involved citizens that is helpful to society (i.e. the community of fellow citizens), rather than, narrowly, as directly remunerated activity. This immediately allows us to recognize the importance of childcare, care for the aged, mentoring, community involvement, and so on. (And, by the way, probably requires us to totally reshape GDP as a measure.) A debate about UBI, for example, becomes much more productive within this framework.

● We will have a much more effective lens to focus on algorithmic and data bias, enabling us to respond with effective long-lasting regulatory frameworks.

● This reboot would also allow us to have a balanced discussion about inequality between generations on a local, regional and global scale, and about the tax regimes designed to address these inequalities. Alternative sources of income — via taxes on spectrum, big data, and other resources which can be construed to be part of the “commons” — are much easier to envisage when we have refreshed our view of the rights and responsibilities of citizens.

● A more active and modern view of citizenship would also completely transform the current debate around the use of our data by large monopolies such as Facebook. It should be a citizen’s responsibility to manage his/her data carefully and thoughtfully. Therefore, involved citizens are more likely to insist on transparency and openness by powerful corporations.

● Finally, a reboot of citizenship will also bring into sharp perspective those qualities which make us human, and which can continue to distinguish us from AIs, at least for the foreseeable future. This is especially important when we look at the changes to education and training that may be required as machines extend their reach. Amongst all the various reports on the future of work there is at least some consensus on which human abilities and skills will remain relevant and useful. These include social and interpersonal skills (teaching, social perceptiveness and coordination), originality, fluency of ideas and communication, active learning and personal development, and system thinking. What better way is there to prioritise developing these characteristics than by reminding ourselves of what all human citizens can contribute?

In conclusion, we are clearly living through a period of disruptive change and experiencing some painful societal upheavals as a result. We are finding it difficult to judge the extent and growth of the change; and are even further away from being able to agree on responses and solutions.

A reboot of concepts of citizenship seems like an impossible exercise to attempt in the middle of this confusion. But in the midst of profound change, what could be more important than to go back to first principles, and refresh our conception of what it means to be an active and responsible human citizen, whilst AI and machines become an ever more powerful reality?